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    Machine Learning Modeling: How It Works and Why It’s Important

    Models are the central output of data science, and they have tremendous power to transform companies, industries, and society.  At the center of every machine learning or...

    Defining Metrics to Drive Machine Learning Model Adoption & Value

    One of the biggest ironies of enterprise data science is that although data science teams are masters at using probabilistic models and diagnostic...

    On Being Model-driven: Metrics and Monitoring

    This article covers a couple of key Machine Learning (ML) vital signs to consider when tracking ML models in production to ensure model reliability,...

    Model Evaluation

    This Domino Data Science Field Note provides some highlights of Alice Zheng’s report, "Evaluating Machine Learning Models", including evaluation...

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